Contact

Email :
Phone number : +33 6 77 54 19 39

7 Rue Diderot, 62000 Arras

Research team

Engineering and Numerical Tools

Research themes

  • Building energy management systems
  • Modeling of processes in buildings
  • Ambient intelligence
  • Smart buildings, and cities

Educational activities

  • Disciplines : Analog and digital electronics,Data science, Artificial intelligence, Physics, and Applications, Student project
  • Niveau : PhD, Engineer, Bachelor

Background

  • PhD Signals, Images, and Automatics
    Paris-Est Créteil University, France, 2020
    MSTIC: Mathematics and Sciences and Technologies of Information and Communication
  • Master of Science Degree in Renewable energy engineering
    Shahid Beheshti University, Tehran, Iran, 2015
  • Bachelor of Science Degree in Power Electrical engineering
    Azad University, Saveh, Markazi, Iran, 2013

Active research program

  • Energy consumption forecasting in buildings by AI techniques
  • Energy performance in smart buildings and smart cities
  • Microgrid modeling

Scientific and laboratory life

  • Membre of LINEACT, 2021-
  • Membre of LISSI, 2016-2020

Selected publications

  • Khalil Al Sayed, Abhinandana Boodi, Roozbeh Sadeghian Broujeny, & Karim Beddiar. (2024). Reinforcement learning for HVAC control in intelligent buildings: A technical and conceptual review. Journal of Building Engineering, 95, 110085. https://doi.org/10.1016/j.jobe.2024.110085
  • Sadeghian Broujeny, R.; Ben Ayed, S.; Matalah, M. Energy Consumption Forecasting in a University Office by Artificial Intelligence Techniques: An Analysis of the Exogenous Data Effect on the Modeling. Energies 2023, 16, 4065. https://doi.org/10.3390/en16104065
  • R. Sadeghian Broujeny, K. Madani, A. Chebira, V. Amarger, and L. Hurtard, A Heating Controller Designing Based on Living Space   Heating Dynamic’s Model Approach in a Smart Building. Energies 2021, 14, 998. https://doi.org/10.3390/ en14040998
  • R. Sadeghian Broujeny, K. Madani, A. Chebira, V. Amarger, and L. Hurtard, “Data-Driven Living Spaces’ Heating Dynamics Modeling in Smart Buildings using Machine Learning-Based Identification,” Sensors, vol. 20, no. 4, p. 1071, Feb. 2020 [Online]. Available: http://dx.doi.org/10.3390/s20041071
  • R. Sadeghian Broujeny, K. Madani, A. Chebira, V. Amarger and L. Hurtard, “A Machine-Learning Based Approach for Data-Driven Identification of Heating Dynamics of Buildings’ Living-Spaces,” 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), Metz, France, 2019, pp. 197-202, doi: 10.1109/IDAACS.2019.8924329